Fundamentals of Digital Signal Processing Using MATLAB® – Schilling – 2nd Edition

Description

This second release content spotlights on the essentials of advanced sign transforming with an accentuation on useful applications. So as to inspire understudies, huge numbers of the samples show the preparing of discourse and music. This topic is additionally a center of the course programming that highlights offices for recording and playing sound on a standard PC.

The going with site contains an extensive MATLAB programming bundle called the Fundamentals of Digital Signal Processing (FDSP) tool compartment form 2.0. The FDSP tool compartment incorporates section GUI modules, a far reaching library of DSP capacities, direct access to the majority of the computational cases, figures, and tables, answers for chose issues, and onliine help documentation. Utilizing the intuitive GUI modules, understudies can investigate, come close, and specifically encounter the impacts of sign transforming procedures with no requirement for programming.

Table of Contents

PART I. SIGNAL AND SYSTEM ANALYSIS.

1. SIGNAL PROCESSING.
Motivation. Signals and Systems. Sampling of Continuous-time Signals. Reconstruction of Continuous-time Signals. Prefilters and Postfilters. DAC and ADC Circuits. The FDSP Toolbox. GUI Software and Case Studies. Chapter Summary. Problems.

2. DISCRETE-TIME SYSTEMS IN THE TIME DOMAIN.
Motivation. Discrete-time Signals. Discrete-time Systems. Difference Equations. Block Diagrams. The Impulse Response. Convolution. Correlation. Stability in the Time Domain. GUI Software and Case Studies. Chapter Summary. Problems.

3. DISCRETE-TIME SYSTEMS IN THE FREQUENCY DOMAIN
Motivation. Z-transform Pairs. Z-transform Properties. Inverse Z-transform. Transfer Functions. Signal Flow Graphs. Stability in the Frequency Domain. Frequency Response. System Identification. GUI Software and Case Studies. Chapter Summary. Problems.

4. FOURIER TRANSFORMS AND SIGNAL ANALYSIS.
Motivation. Fourier Series. Discrete-time Fourier Transform (DTFT). Discrete Fourier Transform (DFT). Fast Fourier Transform (FFT). Fast Convolution and Correlation. White Noise. Auto-correlation. Zero Padding and Spectral Resolution. Spectrogram. Power Density Spectrum Estimation. GUI Software and Case Studies. Chapter Summary. Problems.

PART II. DIGITAL FILTER DESIGN.

5. FILTER DESIGN SPECIFICATIONS.
Motivation. Frequency-selective Filters. Linear-phase and Zero-phase Filters. Minimum-phase and Allpass Filters. Quadrature Filters. Notch Filters and Resonators. Narrowband Filters and Filter Banks.
Adaptive Filters. GUI Software and Case Study. Chapter Summary. Problems.

6. FIR FILTER DESIGN.
Motivation. Windowing Method. Frequency-sampling Method. Least-squares Method. Equiripple Filters. Differentiators and Hilbert Transformers. Quadrature Filters. Filter Realization Structures. Finite Word Length Effects. GUI Software and Case Study. Chapter Summary. Problems.

7. IIR FILTER DESIGN.
Motivation. Filter Design by Pole-zero Placement. Filter Design Parameters. Classical Analog Filters. Bilinear Transformation Method. Frequency Transformations. Filter Realization Structures. Finite Word Length Effects. GUI Software and Case Study. Chapter Summary. Problems.

PART III. ADVANCED SIGNAL PROCESSING.

8. MULTIRATE SIGNAL PROCESSING
Motivation. Integer Sampling Rate Converters. Rational Sampling Rate Converters. Multirate Filter Realization Structures. Narrowband Filters and Filter Banks. A Two-channel QMF Bank.
Oversampling ADC. Oversampling DAC. GUI Software and Case Study. Chapter Summary. Problems.

9. ADAPTIVE SIGNAL PROCESSING.
Motivation. Mean Square Error. The Least Mean Square (LMS) Method. Performance Analysis of the LMS Method. Modified LMS Methods. Adaptive FIR Filter Design. The Recursive Least Squares (RLS) Method. Active Noise Control. Nonlinear System Identification. GUI Software and Case Study. Chapter Summary. Problems.

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